Abstract
Wireless Sensor Networks (WSNs) are densely and largely deployed in a variety of environments to sense real-world events. Many approaches have been proposed for collecting sensory data in any wireless sensor networks in a flexible, reliable, and efficient manner. In this study, we design an efficient mobile agent-based model for data gathering in wireless sensor networks to achieve energy and timely collection of sensory information in the target scene. The current focus in wireless sensor networks is placed on energy optimization during data gathering, processing and transmission. Mobile Agents (MAs) as a piece of a program have attracted growing research interest that travels the network from node to node to compute the local data to get useful information globally. Mobile agent’s features such as autonomy, social ability, learning, and more significantly, mobility makes it a chosen technology for information processing in wireless sensor networks and other resource constrained computing environments. The nodes of the sensors are modelled and represented by the states of a Markov chain. The nodes are further grouped into clusters to save the energy of the nodes farther away from the base station. Keywords: Mobile Agents, Sensor Nodes, Wireless Sensor Networks, Clustering. DOI: https://doi.org/10.18267/j.aip.84
Highlights
Recent advances in wireless communications and electronics have led to the development of Wireless Sensor Networks (WSNs)
A wireless sensor network (WSN) consists of spatially distributed autonomous sensor nodes and a communication system that allows automatic data collection, processing and sharing based on the collaborative effort of a large number of sensor nodes
We assume that the state of the source node carrying the mobile agent during this predetermined period of sleeping and waking as the energy consumed during the normal duty cycle
Summary
Recent advances in wireless communications and electronics have led to the development of Wireless Sensor Networks (WSNs). A wireless sensor network (WSN) consists of spatially distributed autonomous sensor nodes and a communication system that allows automatic data collection, processing and sharing based on the collaborative effort of a large number of sensor nodes. The applications of wireless sensor networks are increasing in wide areas of human endeavours. They are especially useful for human operations in unreachable fields and hazardous environments (Dong, 2014). WSNs can produce a measurable response to changes in physical conditions and the primary goal of such networks is to perform distributed sensing tasks. These networks constitutes a new kind of ad hoc networks with a new set of characteristics and challenges.
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